Abstract In the diagnosis of Alzheimer?s disease (AD), cognitive changes have been the core clinical symptoms, but neuropsychiatric symptoms (NPS) such as apathy, depression, and anxiety can also be the earliest manifestations of AD in as many as 88% of affected persons. While alterations of the reward network in apathy and related NPS were observed in various studies, there is relatively limited research studying the underlying biological mechanism linking AD-specific pathology to reward network degeneration and ultimately the development of NPS in AD. With the recent invention of tau PET imaging and revolutionary advances in human connectome imaging techniques, we have the unprecedented opportunity to study AD-specific pathological changes in the reward network and their consequences on the development of NPS. By leveraging existing tau PET and connectome imaging data from two large-scale projects, we will study in this project how tau pathology affects reward network pathways and contributes to the development of NPS in AD patients. We focus on the tau pathology because it has been consistently shown to be more strongly correlated with clinical symptoms than amyloid-?(A?) plaques. Our project also builds upon strong evidence supporting the transynaptic propagation of tau pathology across different brain regions from both animal and human studies. There are two specific aims in this project. 1. To develop the computational tools for systematically mapping the reward network with connectome imaging data. 2. To determine the extent to which reward-related neuropsychiatric symptoms in AD subjects across genetic subtypes can be predicted with tau deposition and connectivity changes in the reward network. With an improved understanding of the propagation of AD pathology within the reward network, we can identify the affected pathways most associated with specific NPS in AD patients, elucidating their mechanisms, facilitating our ability to predict their development, and potentially enhancing our abilities to track response to treatment. All the computational tools developed in this project will be freely distributed to the research community. We believe this will fill an urgent gap in current AD research and greatly benefit the research regarding NPS in AD.